Performing aggregation within a graph can result in simpler, more efficient decision making. For example, aggregation may be performed to simplify a high resolution problem by creating a lower resolution problem that may be easier to solve. However, current techniques for performing aggregation within a graph have been associated with various limitations.
For example, current implementations for performing aggregation within a graph have shown a variety of inefficiencies which may be amplified as data sets utilized during the aggregation increase in size. Furthermore, current implementations may show inefficiencies due to the fact that such implementations may be performed only utilizing serial methodologies. There is thus a need for addressing these and/or other issues associated with the prior art.